This work provides a guideline for a structural approach towards data mining projects in tribology. Due to the specifics of tribological processes, parts of the DMME methodology need to be refined. The refined data mining methodology is applied to an on-going data mining project in tribology aimed at predicting wear rate and coefficient of friction of nitrocarburised coatings. The applied adapted methodology provides an efficient framework for data generation, preparation and analysis. At the same time, it supports and guides interdisciplinary work between data scientists and tribologists.
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